What is the maximum number of results this skill can handle?

The splunk-export skill is specifically designed for high-volume exports exceeding 50,000 rows by using streaming to prevent memory overhead and timeouts.

What file formats are supported for data exports?

You can export Splunk search results in CSV, JSON, XML, or raw event formats depending on your integration needs.

Can I resume an interrupted export?

Yes, the skill includes a checkpoint feature that allows you to resume large data exports exactly where they left off using a local checkpoint file.

Is this skill safe to use on production Splunk instances?

Yes, all export operations are read-only. The skill only writes to a local file for checkpoints and does not modify your Splunk data or configuration.

Splunk High-Volume Data Export

Name: Splunk High-Volume Data Export
Author: grandcamel

bygrandcamel

Analytics & Monitoring

Facilitates efficient, high-volume streaming data extraction and checkpoint-based resumes from Splunk instances.

About

This skill provides a specialized framework for extracting large datasets exceeding 50,000 rows from Splunk using the REST API. It utilizes streaming to maintain efficiency and includes a robust checkpointing system to resume interrupted exports, making it ideal for ETL processes, data backups, and large-scale data analysis tasks where reliability and resource management are paramount.

Key Features

Checkpoint-based resume functionality for reliable long-running exports
High-volume streaming for result sets exceeding 50,000 records
Support for multiple output formats including CSV, JSON, and XML
0 GitHub stars
Pre-export size estimation to preview result counts before processing
Raw event extraction capabilities for granular data analysis

Use Cases

Extracting massive datasets for external data science or machine learning workflows
Performing ETL tasks to move data from Splunk into data warehouses or analytics platforms
Automating scheduled backups or archiving of specific Splunk indexes to local storage

About

Key Features

Checkpoint-based resume functionality for reliable long-running exports
High-volume streaming for result sets exceeding 50,000 records
Support for multiple output formats including CSV, JSON, and XML
0 GitHub stars
Pre-export size estimation to preview result counts before processing
Raw event extraction capabilities for granular data analysis

Use Cases

Extracting massive datasets for external data science or machine learning workflows
Performing ETL tasks to move data from Splunk into data warehouses or analytics platforms
Automating scheduled backups or archiving of specific Splunk indexes to local storage